nep-mst New Economics Papers
on Market Microstructure
Issue of 2020‒10‒12
four papers chosen by
Thanos Verousis
  1. Cross-Venue Liquidity Provision: High Frequency Trading and Ghost Liquidity By Degryse, Hans; De Winne, Rudy; Gresse, Carole; Payne, Richard
  2. Appetite for information and trading behavior By Bellofatto, Anthony; Broihanne, Marie-Hélène; D'Hondt, Catherine
  3. Googlization and retail investors' trading activity By Christophe Desagre; Catherine D'Hondt
  4. Machine learning sentiment analysis, Covid-19 news and stock market reactions By Costola, Michele; Nofer, Michael; Hinz, Oliver; Pelizzon, Loriana
  1. By: Degryse, Hans; De Winne, Rudy; Gresse, Carole; Payne, Richard
    Keywords: High Frequency Trading ; Algorithmic Trading ; Fragmentation ; Ghost Liquidity
    Date: 2019–01–01
    URL: http://d.repec.org/n?u=RePEc:ajf:louvlf:2019001&r=all
  2. By: Bellofatto, Anthony; Broihanne, Marie-Hélène; D'Hondt, Catherine
    Keywords: retail investors ; information acquisition ; financial knowledge ; MiFID
    JEL: D14 D83 G11 G28
    Date: 2019–01–01
    URL: http://d.repec.org/n?u=RePEc:ajf:louvlf:2019002&r=all
  3. By: Christophe Desagre; Catherine D'Hondt
    Keywords: Investor attention ; Google SVI ; Retail investors
    Date: 2020–01–01
    URL: http://d.repec.org/n?u=RePEc:ajf:louvlf:2020004&r=all
  4. By: Costola, Michele; Nofer, Michael; Hinz, Oliver; Pelizzon, Loriana
    Abstract: The possibility to investigate the impact of news on stock prices has observed a strong evolution thanks to the recent use of natural language processing (NLP) in finance and economics. In this paper, we investigate COVID-19 news, elaborated with the "Natural Language Toolkit" that uses machine learning models to extract the news' sentiment. We consider the period from January till June 2020 and analyze 203,886 online articles that deal with the pandemic and that were published on three platforms: MarketWatch.com, Reuters.com and NYtimes.com. Our findings show that there is a significant and positive relationship between sentiment score and market returns. This result indicates that an increase (decrease) in the sentiment score implies a rise in positive (negative) news and corresponds to positive (negative) market returns. We also find that the variance of the sentiments and the volume of the news sources for Reuters and MarketWatch, respectively, are negatively associated to market returns indicating that an increase of the uncertainty of the sentiment and an increase in the arrival of news have an adverse impact on the stock market.
    Keywords: COVID-19 news,Sentiment Analysis,Stock Markets
    JEL: G10 G14 G15
    Date: 2020
    URL: http://d.repec.org/n?u=RePEc:zbw:safewp:288&r=all
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